Processing large amounts of data is a common requirement, and traditional synchronous processing methods often prove to be inefficient, particularly when dealing with enormous datasets. This article introduces an efficient method for processing big data in a multi-threaded asynchronous manner, leveraging a 'as-you-go' approach to dramatically boost processing efficiency and minimize memory usage. This solution is just one possible way to achieve this goal, and it can be adapted and extended to suit various use cases and requirements.
In the next sections, we will dive deeper into the problem statement, present a hypothetical scenario, propose the solution, provide sample code, and discuss the benefits and trade-offs of this approach.